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The purpose of this study is to examine the impact of the pandemic on the stability of the financial industry. After a disaster or disease outbreak in a region, the stabilization and recovery of various financial institutions will have a very important role in the overall economic recovery. Moreover, recently there has been a global disease outbreak (Covid-19) which has impacted the economies of various countries, including various financial institutions. This study uses a panel data approach and two estimation procedures, namely fixed effect and OLS to measure the impact of the pandemic on financial industry stability. Panel data used to measure the impact of natural disasters and disease outbreaks on the financial stability of the financial industry is fairly new to the research field, and provides valuable insights for policymakers and industry professionals. The results showed that natural disasters and outbreaks have a significant impact on the financial stability of the financial industry, and these have varying impacts depending on the type of disaster, country, and institution. From the findings of this study, the authors suggest that policymakers consider implementing new measures to mitigate the impact that will arise by improving risk management practices and increasing capital requirements for the financial industry. Future research is expected to focus on developing more comprehensive datasets to improve analysis and understanding of future impacts.

The performance of members of the People's Representative Council (DPR) in carrying out their duties is often criticized. Either because of his policies or because of his personality which is considered less effective. Therefore it is necessary to test whether there is an influence of motivation and organizational culture on the performance of the people's representative council (DPR) with work stress as an intervening variable in Aceh Province. This study uses economics, this research is verification. This research refers to the first rule, so the researcher determines the number of samples using the maximum likelihood estimation method of 81 respondents. The results of the study show that motivation has a very large influence on the performance of the Aceh Province DPR. Because with the motivation of the DPR, they will have enthusiasm in working and carrying out the assigned tasks. In addition, organizational culture also has a very large influence on the performance of the Aceh Provincial Parliament. Because with relevant habits in carrying out their duties. Then the work that has been set will be easier to do. So it can be concluded that motivation and organizational culture have a very large influence on the performance of the Aceh DPR.

The Erlang distribution is a special case of the Gamma distribution with the k shape parameter and the λ rate parameter. In this study, the parameter estimation of the Erlang distribution was carried out using the Maximum Likelihood method. In maximizing the function, an implicit and non-linear form is obtained, then it is solved using the Newton Raphson algorithm. Apart from Newton Raphon, the estimation of parameters was also carried out using the Fisher Scoring algorithm. The Fisher Scoring algorithm is similar to the Newton Raphson algorithm, the difference is that Fisher Scoring uses an matrix information. The result of parameter estimation in Erlang distribution using Newton Raphson algorithm which is applied to outgoing telephone call data that generated by Matlab R2010a software cannot be done simultaneously. Therefore, the parameter assessment is carried out on the k parameter first, then followed by the λ parameter estimation and the parameter and  = 0.6886812 are obtained. Meanwhile, the parameter estimation using the Fisher Scoring algorithm produces an equation that is not different from the Newton Raphson algorithm

Analysis of panel data regression is a regression method to determine the relationship between the independent variable and the dependent variable using combined data, namely between cross-section data and time-series data.Analysis of panel data regression can apply to the processing of rice production estimates for an area including the province of North Sumatera. North Sumatera is one of the provinces in Indonesia, at the very of the population focuses on the agricultural sector as the main livelihood in rice being the primary production. Based on data on the development of rice production at the Agriculture Office of North Sumatra Province, the level of rice production in 2019 for North Sumatra Province reached 4,693,563 Ton/Year.Throught Panel Data Regression Analysis with the three approach methods is Common Effect Model (CEM), Fixed Effect Model (FEM) and Random Effect Model (REM) , the best approach method is obtained, namely the Fixed Effect Model (FEM) with the best estimation model is . The coefficient of determination  of 0.950890, which means that the independent variable affects the dependent variable by 95.08% on rice production.Based on the estimation model, the development of rice production in the next 3 years, namely 2020, 2021 and 2022, has changes of around 39.88% (decrease), 10.68% (increase), 9.89% (increase).

The destinations of this examination are: 1. To portray the workplace, responsibility and execution of representatives at PT Alamjaya Wirasentosa Pematangsiantar. 2. To decide the impact of workplace and obligation to worker execution at PT Alam jaya Wirasen tosa Pematang siantar either all the while or halfway. The exploration configuration utilized is library examination and field research. The populace in this investigation is the whole populace of PT Alamjaya Wirasentosa Pematangsiantar, adding up to 26 individuals. The information utilized are subjective information and quantitative information, and information assortment methods through surveys, meetings and documentation. At that point the information examination procedure utilized the traditional supposition test, subjective distinct investigation and quantitative enlightening examination. The examination results from numerous straight relapse, in particular Ŷ = 1.017 + 1.044X1 + 0.528X2, implying that thhere is a positive impact between workplace and obligation to worker execution. The aftereffects of the connection coefficient examination acquired a worth of R = 0.889, which implies that there is a solid and posiitive connection betwieen workplace and obligation to representative execution. At that point the assurance coefficient esteem = 0.791, implying that the high and low presentation of representatives at PT Alamjaya Wirasentosa Pematangsiantar of 79.1% can be clarified by workplace and responsibility while the leftover 20.09% is impacted by different factors like authoritative culture, correspondence, pay, improvement. profession, administration style, preparing, position fulfillment and different facetors not inspected in this investigation. From the consequences of the preparing an estimation of the survey, the creators presume that the workplace and responsibility applied by PT Alamjaya Wirasentosa Pematangsiantar have a positive and huge impact on representative execution. This is confirmed by synchronous theory testig, where the test outcomes fcount (43.454)> Ftable (3.422) with an importance level of 0.000 <α 0.05.

This research endeavours to delve into the potential of Artificial Intelligence (AI) in bolstering Project Resource Management (PRM), discerning the principal challenges inherent in project resource planning, acquisition, and human as well as physical resource management, while also appraising the utilization of AI tools by project team members (PTM) and their efficacy in daily tasks. This research contributes a theoretical basis for what lies ahead studies in PM and unveils the benefits of AI in task monitoring, scheduling, team assignment, cost estimation, and the monitoring of physical project resource availability. This study employs a mixed-method approach, commencing with an initial literature review to identify project challenges. Data collection is facilitated through the administration of questionnaire surveys and interviews with project managers, encompassing both closed-ended and semi-structured questions. The research reveals that PTM readily embraces the utilization of AI for daily tasks and Project Resource Management can be enhanced through AI.

This research aims to analyze the influence of exchange rate, exports, and  imports on Indonesia's foreign exchange reserves in the period of 1992-2021. The dependent variable is foreign exchange reserves, whereas the independent variables consist of exchange rate, exports, and imports. The research uses secondary data in time series obtained from Indonesia’s World Bank Data. Data are analyzed with VAR (Vector Auto Regression), those analyzed use E-Views 10 apss by including analysis method, which includes stationary tests, stability tests, optimum lag tests, cointegration tests, VAR estimation tests, Engle Granger causality tests, Impulse Response Function (IRF) tests, and Variance Decomposition (VD) tests. The results of the study show that exchange rate variables have a large influence on foreign exchange reserves, while export and import variables have a small effect on foreign exchange reserves.

The most important part in software engineering is a software defect prediction. Software defect prediction is defined as a software prediction process from errors, failures, and system errors. Machine learning methods are used by researchers to predict software defects including estimation, association, classification, clustering, and datasets analysis. Datasets of NASA Metrics Data Program (NASA MDP) is one of the metric software that researchers use to predict software defects. NASA MDP datasets contain unbalanced classes and high dimensional data, so they will affect the classification evaluation results to be low. In this research, data with unbalanced classes will be solved by the AdaCost method and high dimensional data will be handled with the Average Weight Information Gain (AWEIG) method, while the classification method that will be used is the Naïve Bayes algorithm. The proposed method is named AWEIG + AdaCost Bayesian. In this experiment, the AWEIG + AdaCost Bayesian algorithm is compared to the Naïve Bayesian algorithm. The results showed the mean of Area Under the Curve (AUC) algorithm AWEIG + AdaCost Bayesian yields better than just a Naïve Bayes algorithm with respectively mean of AUC values are 0.752 and 0.696.

This study aims to determine the integration level of Southeast Asian stock market with the world stock market using an international capital asset pricing model. The countries that were sampled in this study were Indonesia, Malaysia, Philippines, Singapore and Thailand. The sample period starts from January 2000 until August 2016. This study uses an partially-segmented international capital asset pricing model by including the assumption of residual that were correlated between asset pricing equations. Because of this assumption, the seemingly unrelated regression (SUR) estimation method is more appropriately compared to the ordinary least square (OLS) method. The results of this study indicate that the integration level of Southeast Asian stock market varies. The Singapore and Thailand stock markets are fully integrated with the world stock market, the Indonesian and Malaysian stock markets are partially integrated with the world stock market, while the Philippine stock market is segmented with the world stock market. This finding shows the difference in the effectiveness of the stock market liberalization process in Southeast Asia

This research was conducted to examine the effect of Capital Adequacy Ratio (CAR), Loan to Deposit Ratio (LDR),Net Interest Margin (NIM), Non Performing Loans (NPL) to the Profitability of Foreign Exchange Banks. This research was set 5 years from the period 2013-2017. The population of this research used35 Foreign Exchange Banks listed on the Bank Indonesia. The facts used comes from the annual financial statements of 35 Foreign Exchange Banks. Data analysis using panel data regression analysis. To choose estimation of Fixed Effect Model (FEM) and Random Effect Model (REM) using Hausman Test technique. The results of data analysis using the help of E-Views software, based on the Hausman Test, are recommended to use Random Effect Model (REM). The results of data analysis show that 1) Capital Adequacy Ratio (CAR) hasno effect on profitability (ROA), 2) Loan to Deposit Ratio (LDR) has a  positiveeffect and significant on profitability (ROA), 3) Net Interest Margin (NIM) has a positive effect on profitability (ROA), 4) Non Performing Loans (NPL) has a negative effecton profitability (ROA).  Key Words :  return on asset, capital adequacy ratio, loan to deposit ratio , net interest margin, non performing loan.

The research want to analysis about corruption and economic growth. The method of analysis use pooling data. Number of cross-section data are 33 provinces and times-series data are three years. The best model obtained from redundant fixed effect test and correlated random effects-Hausman test. The model used an estimation methodin whichthe cross-section is none and the period is fixed. Based on regression output, corruption has negative significant to Indonesia economic growth. So,corruption becomea grease of wheel for indonesia economics. The meaning is corruption increase economic growth. There areten provincesin which theCPI variable significantly to economic growth. Two provinceshave negatif significant and others positif significant to economic growth. If the ten provinces removed from regression,CPI becomes insignificant. So, the ten provinces have big influence to Indonesia economics, especially in CPI.Key words: CPI, economics growth, pooling data, none, fixed, and grease of wheel

The purpose of this study is to estimate the effect of exchange rate volatility on international tradein Indonesia. The measure of volatility show that the exchange rate has ARCH and GARCHeffect. So, volatility of the exchange rate influenced by current and previous exchange ratevolatility.Sum ofARCH and GARCH coefficient show that the exchange rate has persistentvolatile. Estimation result indicate that exchange rate volatility is not significant. While, GDPworld and GDP Indonesia influencepositivesignificant on international trade, not only in shortterm but also in long term.Key Words: volatility, ARCH, GARCH, Persistent volatile, international trade, exchange rate, andGDP